Certain embodiments of the present invention relate to an ultrasound machine for generating and displaying an image of moving structure. More particularly, certain embodiments relate to adaptively color mapping an image of moving structure such as heart tissue.
Echocardiography is a branch of the ultrasound field that is currently a mixture of subjective image assessment and extraction of key quantitative parameters. Evaluation of cardiac wall function has been hampered by a lack of well-established parameters that may be used to increase the accuracy and objectivity in the assessment of, for example, coronary artery diseases. Stress echo is such an example. It has been shown that the subjective part of wall motion scoring in stress echo is highly dependent on operator training and experience. It has also been shown that inter-observer variability between echo-centers is unacceptably high due to the subjective nature of the wall motion assessment.
Much technical and clinical research has focused on the problem and has aimed at defining and validating quantitative parameters. Encouraging clinical validation studies have been reported, that indicate a set of new potential parameters that may be used to increase objectivity and accuracy in the diagnosis of, for instance, coronary artery diseases. Many of the new parameters have been difficult or impossible to assess directly by visual inspection of the ultrasound images generated in real-time. The quantification has typically required a post-processing step with tedious, manual analysis to extract the necessary parameters.
Much of the prior art describes techniques for non-adaptive color mapping of estimated imaging parameters such as tissue velocity and strain rate. A fixed mapping of a continuous range of color hues is typically used to indicate positive velocities or strain rates and a second fixed mapping of a continuous range of color hues is used to indicate negative velocities or strain rates. This type of color encoding makes it easy to identify reversals in velocities or strain rates. Timing information related to the velocity or strain rate reversals is also easy to extract from M-mode displays.
However, the non-adaptive color schemes in the prior art are not well suited for visual determination of other parameters, such as quantitative velocities or strain rates. Typically, a Nyquist velocity and associated pulse repetition frequency is set in order to avoid aliasing. Most of the actual velocities present are only a small fraction of the peak velocity which, in cardiac imaging from apex, typically may be measured at the mitral ring during the E-wave in diastole. As a result, most regions in the image are mapped with only small variations of the color hue mapped to lower positive and/or lower negative velocities. Quantitative assessment of parameters such as velocities or strain rates from 2-D images has been difficult, even in lucky situations, with a good spread of measured imaging parameters. It has, therefore, been necessary to resort to post-processing techniques and manual extraction of the digital information used in the color encoding for estimation of quantitative values.
Certain adaptive techniques have been previously applied to flow signals. For example, a method in U.S. Pat. No. 6,017,309 to Washburn et al. describes color coding of color flow data relating to fluid, such as blood. As explained in Col. 8, lines 25-54, an Auto Color Map Threshold/Compression Algorithm allows the stored color map threshold to be reset for better detection of low velocity or low power flow and allows the map to be re-mapped or compressed over the range of color flow data actually present. Two algorithms are provided: one for velocity mode and one for PDI mode. For the velocity mode, N frames of color flow data are collected from cine memory 28C and formed into a composite histogram as shown in FIG. 8. The N frames are required to account for flow pulsatility. Then, the fixed map threshold is received by the algorithm from memory at a terminal 31 and is adjusted, if necessary, and the color map is re-created to apply more colors of the map across the full range of data in the composite histogram in a linear manner. As FIG. 8 shows, the positive velocity data in the composite histogram does not cover the full range of 0 to 127, but instead covers some smaller range in-between. The algorithm calculates the statistics of the histogram data and sets the new map threshold to be x standard deviations below the mean. The value of x is determined per application to maximize low velocity flow detection while minimizing low velocity artifacts such as residual wall or tissue motion. The negative map threshold similarly is set for negative velocities based on the statistics of the negative velocity histogram. In this example of FIG. 8, the velocity color map is re-created (effectively linearly compressed) to apply more of its colors across the range of data in the composite histogram, taking into account the map threshold as a reference end point.
Methods in U.S. Pat. No. 6,071,241 to Washburn et al., U.S. Pat. No. 6,126,605 to Washburn et al., and U.S. Pat. No. 6,162,176 to Washburn et al., each describe an ultrasound color flow imaging system programmed to optimize display images of power and velocity by automatically adjusting thresholds by using histograms and samplings of color flow data.
A method in U.S. Pat. No. 6,120,451 to Washburn et al. describes an ultrasound color flow imaging system programmed to optimize display images of power and velocity by automatically adjusting thresholds by using histograms.
None of the foregoing patents, however, describe or suggest any color mapping technique for generating an ultrasound display of moving structure that uses the full dynamic range of the color map. The foregoing patents relate to displays representing moving fluid, such as blood and only perform simple linear compressions of the color map dynamic range or pre-determined non-linear compressions.
A need exists for a robust approach to more easily visualize tissue motion parameter information, such as strain rate, in a two-dimensional ultrasound image such that more of the tissue motion parameter information is broken out and is observed.